The underlying ideas for the D-Wave approach arose from experimental results in condensed matter physics, and in particular work on quantum annealing in magnets performed by Dr. Gabriel Aeppli.[8] These ideas were later recast in the language of quantum computation by MIT physicists Ed Farhi, Seth Lloyd, Terry Orlando and Bill Kaminsky, whose publications in 2000[9] and 2004[10] provided both a theoretical model for quantum computation that fit with the earlier work in quantum magnetism (specifically the adiabatic quantum computing model and quantum annealing, its finite temperature variant), and a specific enablement of that idea using superconducting flux qubits which is a close cousin to the designs D-Wave produced. In order to understand the origins of much of the controversy around the D-Wave approach, it is important to note that the origins of the D-Wave approach to quantum computation arose not from the conventional quantum information field, but from experimental condensed matter physics.

In January 2017, D-Wave has released the D-Wave 2000Q and Qbsolv. Qbsolv[20][21][22] is a piece of open-source software that solves QUBO problems on both company's quantum processors and classic hardware architectures.

D-Wave was founded by Haig Farris (former chair of board), Geordie Rose (CTO and former CEO), Bob Wiens (former CFO), and Alexandre Zagoskin[23] (former VP Research and Chief Scientist). Farris taught a business course at the University of British Columbia (UBC), where Rose obtained his Ph.D., and Zagoskin was a postdoctoral fellow. The company name refers to their first qubit designs, which used d-wave superconductors.

D-Wave operated from various locations in Vancouver, British Columbia, and laboratory spaces at UBC before moving to its current location in the neighboring suburb of Burnaby. D-Wave also has offices in Palo Alto and Vienna, USA.[citation needed]

The first application, an example of pattern matching, performed a search for a similar compound to a known drug within a database of molecules. The next application computed a seating arrangement for an event subject to compatibilities and incompatibilities between guests. The last involved solving a Sudoku puzzle.[citation needed]

According to the company, a conventional front end running an application that requires the solution of an NP-complete problem, such as pattern matching, passes the problem to the Orion system.

According to Geordie Rose, founder and Chief Technology Officer of D-Wave, NP-complete problems "are probably not exactly solvable, no matter how big, fast or advanced computers get"; the adiabatic quantum computer used by the Orion system is intended to quickly compute an approximate solution.[37]

On December 8, 2009, at the Neural Information Processing Systems (NIPS) conference, a Google research team led by Hartmut Neven used D-Wave's processor to train a binary image classifier.[citation needed]

On May 11, 2011, D-Wave Systems announced the D-Wave One, an integrated quantum computer system running on a 128-qubit processor. The processor used in the D-Wave One code-named "Rainier", performs a single mathematical operation, discrete optimization. Rainier uses quantum annealing to solve optimization problems. The D-Wave One is claimed to be the world's first commercially available quantum computer system.[38]
The price is approximately US$10,000,000.[3]

A research team led by Matthias Troyer and Daniel Lidar found that, while there is evidence of quantum annealing in D-Wave One, they saw no speed increase compared to classical computers. They implemented an optimized classical algorithm to solve the same particular problem as the D-Wave One.[39][40]

On May 25, 2011, Lockheed Martin signed a multi-year contract with D-Wave Systems to realize the benefits based upon a quantum annealing processor applied to some of Lockheed's most challenging computation problems. The contract included purchase of the D-Wave One quantum computer, maintenance, and associated professional services.[41]

In August 2012, a team of Harvard University researchers presented results of the largest protein-folding problem solved to date using a quantum computer. The researchers solved instances of a lattice protein folding model, known as the Miyazawa–Jernigan model, on a D-Wave One quantum computer.[42][43]

In early 2012, D-Wave Systems revealed a 512-qubit quantum computer, code-named Vesuvius,[44] which was launched as a production processor in 2013.[45]

In May 2013, Catherine McGeoch, a consultant for D-Wave, published the first comparison of the technology against regular top-end desktop computers running an optimization algorithm. Using a configuration with 439 qubits, the system performed 3,600 times as fast as CPLEX, the best algorithm on the conventional machine, solving problems with 100 or more variables in half a second compared with half an hour. The results are presented at the Computing Frontiers 2013 conference.[46]

In May 2013 it was announced that a collaboration between NASA, Google and the USRA launched a Quantum Artificial Intelligence Lab at the NASA Advanced Supercomputing Division at Ames Research Center in California, using a 512-qubit D-Wave Two that would be used for research into machine learning, among other fields of study.[16][48]

On August 20, 2015, D-Wave released general availability of their D-Wave 2X computer, with 1,000 qubits in a Chimera graph architecture (although, due to magnetic offsets and manufacturing variability inherent in the superconductor circuit fabrication fewer than 1,152 qubits are functional and available for use. The exact number of qubits yielded will vary with each specific processor manufactured.) This was accompanied by a report comparing speeds with high-end single threaded CPUs.[49] Unlike previous reports, this one explicitly stated that question of quantum speedup was not something they were trying to address, and focused on constant-factor performance gains over classical hardware. For general-purpose problems, a speedup of 15x was reported, but it is worth noting that these classical algorithms benefit efficiently from parallelization—so that the computer would be performing on par with, perhaps, 30 high-end single-threaded cores.

The D-Wave 2X processor is based on a 2,048-qubit chip with half of the qubits disabled; these were activated in the D-Wave 2000Q.[50][51]

"Their claimed speedup over classical algorithms appears to be based on a misunderstanding of a paper my colleagues van Dam, Mosca and I wrote on "The power of adiabatic quantum computing." That speed up unfortunately does not hold in the setting at hand, and therefore D-Wave's "quantum computer" even if it turns out to be a true quantum computer, and even if it can be scaled to thousands of qubits, would likely not be more powerful than a cell phone."

Wim van Dam, a professor at UC Santa Barbara, summarized his opinion as of 2008 in the journal Nature Physics:[58] "At the moment it is impossible to say if D-Wave's quantum computer is intrinsically equivalent to a classical computer or not. So until more is known about their error rates, caveat emptor is the least one can say".

An article in the May 12, 2011, edition of Nature gives details which critical academics say proves that the company's chips do have some of the quantum mechanical properties needed for quantum computing.[59][60] Prior to the 2011 Nature paper, D-Wave was criticized for lacking proof that its computer was in fact a quantum computer. Nevertheless, questions were raised[61] and later answered[62] regarding experimental proof of quantum entanglement inside D-Wave devices.

Former MIT professor Scott Aaronson, who has described himself as "Chief D-Wave Skeptic", said that D-Wave's 2007 demonstration did not prove anything about the workings of the Orion computer, and that its marketing claims were deceptive.[63] In May 2011 he said that he was "retiring as Chief D-Wave Skeptic",[64] and reporting his "skeptical but positive" views based on a visit to D-Wave in February 2012. Aaronson said that one of the most important reasons for his new position on D-Wave was the 2011 Nature article.[61][65][66] In May 16, 2013 he resumed his skeptic post. He criticizes D-Wave for blowing results out of proportion on press releases that claim speedups of three orders of magnitude, in light of a paper[40] by scientists from ETH Zurich reporting a 128-qubit D-Wave computer being outperformed by a factor of 15 using regular digital computers and applying classical metaheuristics (particularly simulated annealing) to the problem that D-Wave's computer was specifically designed to solve.[39]

On May 16, 2013, NASA and Google, together with a consortium of universities, announced a partnership with D-Wave to investigate how D-Wave's computers could be used in the creation of artificial intelligence. Prior to announcing this partnership, NASA, Google, and Universities Space Research Association put a D-Wave computer through a series of benchmark and acceptance tests, which it passed.[16] Independent researchers found that D-Wave's computers could solve some problems as much as 3,600 times faster than particular software packages running on conventional digital computers.[16] Other independent researchers found that different software packages running on a single core of a desktop computer can solve those same problems as fast or faster than D-Wave's computers (at least 12,000 times faster for quadratic assignment problems, and between 1 and 50 times faster for quadratic unconstrained binary optimization problems).[67]

In January 2014, researchers at UC Berkeley and IBM published a classical model reproducing the D-Wave machine's observed behavior, suggesting that it may not be a quantum computer.[68]

In March 2014, researchers at University College London and the University of Southern California (USC) published a paper comparing data obtained from a D-Wave Two computer with three possible explanations from classical physics and one quantum model. They found that their quantum model was a better fit to the experimental data than the Shin–Smith–Smolin–Vazirani classical model, and a much better fit than any of the other classical models. The authors conclude that "This suggests that an open system quantum dynamical description of the D-Wave device is well-justified even in the presence of relevant thermal excitations and fast single-qubit decoherence."[69]

In May 2014, researchers at D-Wave, Google, USC, Simon Fraser University, and National Research Tomsk Polytechnic University published a paper containing experimental results that demonstrated the presence of entanglement among D-Wave qubits. Qubit tunneling spectroscopy was used to measure the energy eigenspectrum of two and eight-qubit systems, demonstrating their coherence during a critical portion of the quantum annealing procedure.[70]

A study published in Science in June 2014,[71] described as "likely the most thorough and precise study that has been done on the performance of the D-Wave machine"[72] and "the fairest comparison yet",[citation needed] attempted to define and measure quantum speedup. Several definitions were put forward as some may be unverifiable by empirical tests, while others, though falsified, would nonetheless allow for the existence of performance advantages. The researchers, led by Matthias Troyer at the Swiss Federal Institute of Technology in Zurich, said that they found "no quantum speedup" across the entire range of their tests, and only inconclusive results when looking at subsets of the tests. Further work[73] has advanced understanding of these test metrics and their reliance on equilibrated systems.
There remain open questions regarding quantum speedup. The ETH reference in the previous section is just for one class of benchmark problems. Potentially
there may be other classes of problems where quantum speedup might occur. Researchers at Google, NASA, LANL, USC, Texas
A&M, and D-Wave are working to find such problem classes.[74]

^D-Wave Systems: D-Wave Two Quantum Computer Selected for New Quantum Artificial Intelligence Initiative, System to be Installed at NASA's Ames Research Center, and Operational in Q3, [3], May 16, 2013